Gerald Wang

About

Gerald J. Wang is an Assistant Professor of Civil and Environmental Engineering at Carnegie Mellon University, having joined the faculty in Fall 2019. He completed his Ph.D. in Mechanical Engineering and Computation at the Massachusetts Institute of Technology (MIT), where he conducted research under the guidance of Professor Nicolas G. Hadjiconstantinou. His doctoral work focused on the theoretical and computational modeling of fluid transport phenomena under nanoscale confinement. From 2014 to 2018, he was recognized as a U.S. Department of Energy Computational Science Graduate Fellow (CSGF). Following his Ph.D., Professor Wang performed postdoctoral research with the late Professor James W. Swan in Chemical Engineering at MIT, where he studied the role of friction in dense colloidal suspensions. Prior to his graduate studies, he earned an S.M. in Mechanical Engineering from MIT in 2015 and dual B.S. degrees in Mechanical Engineering and in Mathematics & Physics from Yale University in 2013, where he worked with Professors Nicholas T. Ouellette and Sarah M. Demers. Professor Wang's research expertise lies in nanoscale fluid dynamics and computational modeling, with a focus on understanding fluid transport and frictional phenomena at the nanoscale.

Research topics

• Radiology
• Internal medicine
• Medicine
• Surgery

Selected publications

• Towards realizing nano-enabled precision delivery in plants

  Nature Nanotechnology · 2024-06-06 · 110 citations

  reviewOpen access
  PublisherOA PDFDOI

• Diversity, Equity, and Inclusion in Civil and Environmental Engineering Education: Social Justice in a Changing Climate

  2021 ASEE Virtual Annual Conference Content Access Proceedings · 2024-02-20 · 20 citations

  articleOpen accessSenior author

  Her research is focused on applying optimization and decision analysis tools to evaluate the sustainability, equity, and reliability of power systems in the US and Sub-Saharan Africa. One of her current NSF-

  PublisherOA PDFDOI

• Polymer encapsulation via initiated chemical vapor deposition (iCVD) to enhance stability of Ti ₃ C ₂ T <i> _x </i> MXene-based formaldehyde sensors

  Science Advances · 2025-07-11 · 17 citations

  articleOpen access

  MXene is a class of compounds known for its superior electrical properties and versatile surface chemistries. However, its susceptibility to oxidation-induced degradation under ambient conditions prevents its incorporation into devices. In this work, we enhance the stability of MXene-based devices through encapsulation. We developed a sensor based on a heterojunction of Ti 3 C 2 T x MXene and silver nanoparticles for formaldehyde detection. This sensor is then encapsulated in poly(1,3,5,7-tetrav…

  PublisherDOI

• Phonon mode resolved anharmonic heat capacity of solids

  Physical review. B./Physical review. B · 2025-02-05 · 9 citations

  article

  We develop and validate a lattice dynamics framework to include anharmonic effects in the calculation of mode-level phonon heat capacities. To capture anharmonicity, the phonons are renormalized using a temperature-dependent effective potential and a proposed approach based on instantaneous normal modes. Ground-truth total heat capacities are obtained from molecular dynamics simulations. For Lennard-Jones argon (Stillinger-Weber silicon), the deviation of the potential energy contribution to the…

  PublisherDOI

• Getting over the hump with KAMEL-LOBE: Kernel-averaging method to eliminate length-of-bin effects in radial distribution functions

  The Journal of Chemical Physics · 2023-06-09 · 5 citations

  articleSenior author

  Radial distribution functions (RDFs) are widely used in molecular simulation and beyond. Most approaches to computing RDFs require assembling a histogram over inter-particle separation distances. In turn, these histograms require a specific (and generally arbitrary) choice of discretization for bins. We demonstrate that this arbitrary choice for binning can lead to significant and spurious phenomena in several commonplace molecular-simulation analyses that make use of RDFs, such as identifying p…

  PublisherDOI

Frequent coauthors

• Sarah Christian

  Stanford University

  45 shared

• Katherine A. Flanigan

  Carnegie Mellon University

  42 shared

• J. Moore

  Carnegie Mellon University

  39 shared

• Douglas S. Scherr

  Institute of Clinical and Experimental Medicine

  38 shared

• Fethiye Ozis

  Northern Arizona University

  36 shared

• Sherven Sharma

  34 shared

• Steven M. Dubinett

  30 shared

• David A. Green

  University of British Columbia

  28 shared

Labs

• M5 LabPI

  The M5 Lab focuses on theoretical and computational modeling of fluid transport phenomena under nanoscale confinement.

Education

• B.S., Mechanical Engineering, Mathematics & Physics

  Yale University

  2013

• Other, Mechanical Engineering

  Massachusetts Institute of Technology

  2015

• Ph.D., Mechanical Engineering and Computation

  Massachusetts Institute of Technology

  2019

Awards & honors

• 2024 CMU Teaching Innovation Award for 'Participation Shouto…

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